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We introduce a class of information measures based on group entropies, allowing us to describe the information-theoretical properties of complex systems. These entropic measures are nonadditive, and are mathematically deduced from a series…

Statistical Mechanics · Physics 2019-10-21 Piergiulio Tempesta , Henrik Jeldtoft Jensen

Geometry and topology have generated impacts far beyond their pure mathematical primitive, providing a solid foundation for many applicable tools. Typically, real-world data are represented as vectors, forming a linear subspace for a given…

Quantum Physics · Physics 2024-05-01 Nhat A. Nghiem

We propose a method to derive the stationary size distributions of a system, and the degree distributions of networks, using maximisation of the Gibbs-Shannon entropy. We apply this to a preferential attachment-type algorithm for systems of…

Physics and Society · Physics 2020-03-17 Cornelia Metzig , Caroline Colijn

Many complex systems are characterized by non-Boltzmann distribution functions of their statistical variables. If one wants to -- justified or not -- hold on to the maximum entropy principle for complex statistical systems (non-Boltzmann)…

Statistical Mechanics · Physics 2009-11-13 Stefan Thurner , Rudolf Hanel

Entropy rate is a real valued functional on the space of discrete random sources which lacks a closed formula even for subclasses of sources which have intuitive parameterizations. A good way to overcome this problem is to examine its…

Information Theory · Computer Science 2015-01-14 Alexander Schönhuth

Maximum entropy modeling is a flexible and popular framework for formulating statistical models given partial knowledge. In this paper, rather than the traditional method of optimizing over the continuous density directly, we learn a smooth…

Methodology · Statistics 2017-05-01 Gabriel Loaiza-Ganem , Yuanjun Gao , John P. Cunningham

We study quantum Dirichlet forms and the associated symmetric quantum Markov semigroups on noncommutative $L^2$ spaces. It is known from the work of Cipriani and Sauvageot that these semigroups induce a first order differential calculus,…

Operator Algebras · Mathematics 2021-08-13 Melchior Wirth

The variation distance closure of an exponential family with a convex set of canonical parameters is described, assuming no regularity conditions. The tools are the concepts of convex core of a measure and extension of an exponential…

Probability · Mathematics 2007-05-23 Imre Csiszar , Frantisek Matus

The number of times that we can access a system to extract information via quantum metrology is always finite, and possibly small, and realistic amounts of prior knowledge tend to be moderate. Thus theoretical consistency demands a…

Quantum Physics · Physics 2021-12-02 Jesús Rubio

Co-compact entropy is introduced as an invariant of topological conjugation for perfect mappings defined on any Hausdorff space(compactness and metrizability not necessarily required). This is achieved through the consideration of…

Dynamical Systems · Mathematics 2015-06-12 Zheng Wei , Yangeng Wang , Guo Wei

This thesis synthesizes probability and entropic inference with Quantum Mechanics (QM) and quantum measurement [1-6]. It is shown that the standard and quantum relative entropies are tools designed for the purpose of updating probability…

Quantum Physics · Physics 2018-04-25 Kevin Vanslette

Different types of two- and three-dimensional representations of a finite metric space are studied that focus on the accurate representation of the linear order among the distances rather than their actual values. Lower and upper bounds for…

Combinatorics · Mathematics 2007-05-23 Jobst Heitzig

This paper introduces a comprehensive framework for complex-valued probability measures and explores their novel applications in information theory and statistical analysis. We define a complex probability measure as a phase-modulated…

Information Theory · Computer Science 2026-03-16 Siang Cheng , Hejun Xu , Tianxiao Pang

The time decay of fully discrete finite-volume approximations of porous-medium and fast-diffusion equations with Neumann or periodic boundary conditions is proved in the entropy sense. The algebraic or exponential decay rates are computed…

Numerical Analysis · Mathematics 2013-03-18 Claire Chainais-Hillairet , Ansgar Jüngel , Stefan Schuchnigg

Non-Hermitian systems with parity-time ($\mathcal{PT}$) symmetry give rise to exceptional points (EPs) with exceptional properties that arise due to the coalescence of eigenvectors. Such systems have been extensively explored in the…

The various entropy bounds that exist in the literature suggest that spacetime is fundamentally discrete, and hint at an underlying relationship between geometry and "information". The foundation of this relationship is yet to be uncovered,…

General Relativity and Quantum Cosmology · Physics 2009-11-11 D. Rideout , S. Zohren

We generalize, improve and unify theorems of Rumin, and Maassen--Uffink about classical entropies associated to quantum density matrices. These theorems refer to the classical entropies of the diagonals of a density matrix in two different…

Mathematical Physics · Physics 2015-05-30 Rupert L. Frank , Elliott H. Lieb

We study the dynamics of piecewise affine surface homeomorphisms from the point of view of their entropy. Under the assumption of positive topological entropy, we establish the existence of finitely many ergodic and invariant probability…

Dynamical Systems · Mathematics 2009-09-29 Jerome Buzzi

When constructing models of the world, we aim for optimal compressions: models that include as few details as possible while remaining as accurate as possible. But which details -- or features measured in data -- should we choose to include…

Quantitative Methods · Quantitative Biology 2025-05-06 David P. Carcamo , Nicholas J. Weaver , Purushottam D. Dixit , Christopher W. Lynn

We examine a class of deep learning models with a tractable method to compute information-theoretic quantities. Our contributions are three-fold: (i) We show how entropies and mutual informations can be derived from heuristic statistical…

Machine Learning · Computer Science 2020-01-22 Marylou Gabrié , Andre Manoel , Clément Luneau , Jean Barbier , Nicolas Macris , Florent Krzakala , Lenka Zdeborová
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